Last few decades have witnessed a rapid development in robotic technology. Different types of intelligent machines which facilitate various tasks in industry environment are becoming popular. This paper focuses on designing a low cost coconut tree climbing and harvesting robot. The kinematics and the motion of the robot are designed by referring to the motion of coconut harvester. The robot consists of two segments joined by a pair of threaded rods coupled to motors. The mechanical frame is designed in draft sight software and is implemented using aluminum segments and threaded rods. It has two arms driven by motors for holding. Locomotion of the robot is achieved using six motors out of which four motors are used in two hands and other two are used for upward and downward motion. The other part is a robotic arm for cutting down the coconuts. The robotic arm is attached on top of the climbing part. The operation of the cutting arm is done manually from the ground using a remote. The robot is automated using Arduino-Uno, motor H-bridge drivers, current and level sensors and other supporting circuits. The forward and the reverse motion of the motors are controlled by the Arduino through driver modules. Robot has automatic and manual functions fully controlled by the end-user. This paper has taken into account of the safety, reliability and the ease of use. A locomotion algorithm is developed to provide the robot with an autonomous capability for climbing. The prototype of the robot is implemented and tested successfully

Nowadays, more than one power source is needed to fulfil the power demand for electric vehicles. The multiple sources enhance reliability regarding the cruising range and decrease the charging cost. However, the inclusion of multi-sources generally gives rise to issues in the controller unit, such as slow response due to the immediate changes in load and power conversion complexity while switching the sources. This paper presents a novel intelligent control scheme based on fuzzy logic to mitigate this issue. The proposed controller includes a solar panel, a fuel cell, and a battery as input source. In this work, to examine the instantaneous reference currents from the sources and to manage power for the electric vehicle motor, a permanent magnet synchronous machine (PMSM) is considered. The proposed controller performs real-time power management, Maximum power point tracking (MPPT) for the PV system, and load calculations based on vehicle dynamics. The proposed work explores power management techniques for efficient control by utilizing real-time irradiance data from the Solcast website and drive cycle data collected at a university campus. Finally, the proposed controller was developed using MATLAB/Simulink and implemented as a hardware investigation with the LabVIEW tool and FPGA controller for a 1 kW PMSM to validate that the controller enables consistent power split operation in different load conditions.

The fault detection and isolation of generators used in wind turbines gathering interest as to maximize the reliability and avail of distributed energy systems with recent unmatched growth in construction of offshore wind farms. In particular it is interested in performing fault detection and isolation (FDI) of incipient faults affecting the measurements of the three-phase signals (currents) in a controlled DFIG and PMSG. Although different authors have dealt with FDI for sensors in induction machines and in DFIGs, most of them rely on the machine model with constant parameters. However, the parameter uncertainties due to changes in the operating conditions will produce degradation in the performance of such FDI systems. The robust techniques to detect faults are exist but there is a need of extra sensor. This paper proposed a systematic methodology for the design of sensor FDI systems with the following characteristics: i) capable of detecting and isolating incipient additive (bias) faults, ii) robust against changes in the references/disturbances affecting the controlled DFIG and PMSG as well as modeling/parametric uncertainties, iii) residual generation system based on a multi-observer strategy to enhance the isolation process, The designed sensor FDI systems have been validated using measured voltages, as well as simulated data from a controlled DFIG. First the state space models of DFIG and PMSM explained followed by kalman filter introduction and current sensor fault detection using a bank of kalman filter named dedicated Observer Scheme and generalized Observer scheme to detect simultaneous and multiple faults was theorized and simulated using MATLAB simulation tool .The simulation results were summarized with and without Sensor fault

The modeling of a solar PV system is challenging due to its nonlinear current vs. voltage characteristics. Although various optimization techniques have been applied for the parameter estimation of the solar PV system, there is still a scope to attain the best-optimized results. This paper uses a new meta-heuristic optimization algorithm and a classical technique named Ali Baba and the Forty Thieves (AFT) with Newton Rapson (NR) method to estimate solar PV system parameters. The well-known story of Ali Baba and the Forty Thieves has inspired the AFT. Besides, the inappropriate objective function used in earlier research to extract parameters from solar PV models is recognized. The experimental findings demonstrate that the suggested approach performs better when compared to state-of-the-art algorithms. Between the measured data and the computed data for AFT, the root mean square error values for the five PV models, such as single diode model (SDM), double diode model (DDM), Photowatt-PWP201, STM6-40/36, and STP6-120/36, are respectively 7.72×10⁻⁰⁴±6.121×10⁻¹⁶, 7.412×10⁻⁰⁴±9.52×10⁻⁰⁶, 2.052×10⁻⁰³±3.05×10⁻¹⁷, 0.001721922±2.19×10⁻¹⁷, and 0.014450817±3.42×10⁻¹⁶. In terms of accuracy, the obtained results indicate that the proposed AFT algorithm is more efficient than the other optimization techniques available in the literature. The excellent correlation between the estimated parameters from characteristic curves and observed data for SDM, DDM, Photowatt-PWP201, STM6-40/36, and STP6-120/36 demonstrates that the proposed AFT is a potential option among the techniques available in the literature. The Friedman and Wilcoxon tests have been used to assess the statistical validity of the proposed algorithms.

Due to the increasing number of direct current (DC) loads in electric vehicles (EVs), DC–DC converters are widely used in EV applications. Hence, a DC distribution system with DC–DC converters is more efficient. A three-phase interleaved step-up DC–DC converter (ISC) has been proposed for use in electric vehicles. Other uses of the proposed ISC converter include aircraft, satellites, industrial, and traction drives. The proposed converter is subjected to a thorough frequency response study, which is explained in detail. The design technique recommends the proper quantity of switches to be used in the system. The reduction in the number of switches results in a 94% increase in the efficiency of this converter. The economic aspects of ISC, such as cost analysis and its procedure, have been discussed. Design models were checked using MATLAB/Simulink, which was interfaced with the real-time simulator OPAL-RT (OP5700) to ensure that they were appropriate. The results have been presented in detail.